{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Recurrent PG Crypto-Currency Trading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The finance module has been deprecated in mpl 2.0 and will be removed in mpl 2.2. Please use the module mpl_finance instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n",
      "/usr/local/lib/python3.5/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.finance as mpf\n",
    "from matplotlib.pylab import date2num\n",
    "from HuobiServices import *\n",
    "from DataUtils import *\n",
    "import talib\n",
    "import tensorflow as tf\n",
    "from tqdm import tqdm\n",
    "import seaborn as sns\n",
    "import os\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [],
   "source": [
    "lmap=lambda func,it: list(map(lambda x:func(x),it))\n",
    "lfilter=lambda func,it: list(filter(lambda x:func(x),it))\n",
    "z_score=lambda x:(x-np.mean(x,axis=0))/(np.std(x,axis=0)+1e-5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_tech_data_default(stock, open_name, close_name, high_name, low_name,volume_name='vol'):\n",
    "    open_price = stock[open_name].values\n",
    "    close_price = stock[close_name].values\n",
    "    low_price = stock[low_name].values\n",
    "    high_price = stock[high_name].values\n",
    "    volume = stock[volume_name].values\n",
    "    data = stock.copy()\n",
    "    data['MOM'] = talib.MOM(close_price)\n",
    "    data['HT_DCPERIOD'] = talib.HT_DCPERIOD(close_price)\n",
    "    data['HT_DCPHASE'] = talib.HT_DCPHASE(close_price)\n",
    "    data['sine'], data['leadsine'] = talib.HT_SINE(close_price)\n",
    "    data['inphase'], data['quadrature'] = talib.HT_PHASOR(close_price)\n",
    "    data['ADXR'] = talib.ADXR(high_price, low_price, close_price)\n",
    "    data['APO'] = talib.APO(close_price)\n",
    "    data['AROON_UP'], _ = talib.AROON(high_price, low_price)\n",
    "    data['CCI'] = talib.CCI(high_price, low_price,close_price)\n",
    "    data['PLUS_DI'] = talib.PLUS_DI(high_price, low_price, close_price)\n",
    "    data['PPO'] = talib.PPO(close_price)\n",
    "    data['macd'], data['macd_sig'], data['macd_hist'] = talib.MACD(close_price)\n",
    "    data['CMO'] = talib.CMO(close_price)\n",
    "    data['ROCP'] = talib.ROCP(close_price)\n",
    "    data['fastk'], data['fastd'] = talib.STOCHF(high_price, low_price, close_price)\n",
    "    data['TRIX'] = talib.TRIX(close_price)\n",
    "    data['ULTOSC'] = talib.ULTOSC(high_price, low_price, close_price)\n",
    "    data['WILLR'] = talib.WILLR(high_price, low_price, close_price)\n",
    "    data['NATR'] = talib.NATR(high_price, low_price, close_price)\n",
    "    data['MFI']=talib.MFI(high_price,low_price,close_price,volume)\n",
    "    data['RSI']=talib.RSI(close_price)\n",
    "    data['AD']=talib.AD(high_price,low_price,close_price,volume)\n",
    "    data['OBV']=talib.OBV(close_price,volume)\n",
    "    data['EMA'] = talib.EMA(close_price)\n",
    "    data['SAREXT'] = talib.SAREXT(high_price,low_price)\n",
    "    data['TEMA'] = talib.EMA(close_price)\n",
    "    data = data.drop([open_name, close_name, high_name, low_name,'amount','count'], axis=1)\n",
    "    data = data.dropna().astype(np.float32)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [],
   "source": [
    "class RPG_CryptoNG(object):\n",
    "    def __init__(self, feature_number, action_size=1, hidden_units_number=[128, 64], learning_rate=0.001):\n",
    "        tf.reset_default_graph()\n",
    "        self.s = tf.placeholder(dtype=tf.float32, shape=[None,None, feature_number], name='s')\n",
    "        self.a = tf.placeholder(dtype=tf.int32, shape=[None,None,action_size], name='a')\n",
    "        self.r = tf.placeholder(dtype=tf.float32, shape=[None,None], name='r')\n",
    "        self.s_next=tf.placeholder(dtype=tf.float32, shape=[None,None, feature_number], name='s_next')\n",
    "        self.action_size=action_size\n",
    "        self.a_buffer = []\n",
    "        self.r_buffer = []\n",
    "        self.s_buffer = []\n",
    "        self.s_next_buffer=[]\n",
    "        self.dropout_keep_prob = tf.placeholder(dtype=tf.float32, shape=[], name='dropout_keep_prob')\n",
    "        with tf.variable_scope('rnn_encoder', initializer=tf.contrib.layers.xavier_initializer(uniform=True), regularizer=tf.contrib.layers.l2_regularizer(0.01)):\n",
    "            cell=self._add_GRU(units_number=128,activation=tf.nn.tanh,keep_prob=self.dropout_keep_prob)\n",
    "#             self.rnn_input=tf.expand_dims(self.s,axis=0)\n",
    "            self.rnn_output,_=tf.nn.dynamic_rnn(inputs=self.s,cell=cell,dtype=tf.float32)\n",
    "#             self.rnn_output=tf.unstack(self.rnn_output,axis=0)[0]\n",
    "            \n",
    "        with tf.variable_scope('supervised',initializer=tf.contrib.layers.xavier_initializer(uniform=True), regularizer=tf.contrib.layers.l2_regularizer(0.01)):\n",
    "            self.state_predict = self._add_dense_layer(inputs=self.rnn_output, output_shape=hidden_units_number, drop_keep_prob=self.dropout_keep_prob, act=tf.nn.relu, use_bias=True)\n",
    "            self.state_predict = self._add_dense_layer(inputs=self.rnn_output, output_shape=[feature_number], drop_keep_prob=self.dropout_keep_prob, act=None, use_bias=True)\n",
    "            self.state_loss=tf.losses.mean_squared_error(self.state_predict,self.s_next)\n",
    "            \n",
    "        with tf.variable_scope('policy_gradient',initializer=tf.contrib.layers.xavier_initializer(uniform=True), regularizer=tf.contrib.layers.l2_regularizer(0.01)):\n",
    "#             self.rnn_output=tf.stop_gradient(self.rnn_output)\n",
    "            self.a_prob = self._add_dense_layer(inputs=self.rnn_output, output_shape=hidden_units_number, drop_keep_prob=self.dropout_keep_prob, act=tf.nn.relu, use_bias=True)\n",
    "            self.a_prob = self._add_dense_layer(inputs=self.a_prob, output_shape=[action_size], drop_keep_prob=self.dropout_keep_prob, act=None, use_bias=True)\n",
    "            self.a_out = tf.nn.softmax(self.a_prob,axis=-1)\n",
    "            self.negative_cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(logits=self.a_prob, labels=self.a)\n",
    "            \n",
    "        with tf.variable_scope('train'):\n",
    "            optimizer_rl = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
    "            optimizer_sl = tf.train.AdamOptimizer(learning_rate=learning_rate*2)\n",
    "            self.rlloss = tf.reduce_mean(self.negative_cross_entropy * self.r)\n",
    "            self.slloss=tf.reduce_mean(self.state_loss)\n",
    "            self.rltrain_op = optimizer_rl.minimize(self.rlloss)\n",
    "            self.sltrain_op = optimizer_sl.minimize(self.slloss)\n",
    "        self.init_op = tf.global_variables_initializer()\n",
    "        self.session = tf.Session()\n",
    "        self.saver = tf.train.Saver()\n",
    "    def init_model(self):\n",
    "        self.session.run(self.init_op)\n",
    "    \n",
    "    def _add_dense_layer(self, inputs, output_shape, drop_keep_prob, act=tf.nn.relu, use_bias=True):\n",
    "        output = inputs\n",
    "        for n in output_shape:\n",
    "            output = tf.layers.dense(output, n, activation=act, use_bias=use_bias)\n",
    "            output = tf.nn.dropout(output, drop_keep_prob)\n",
    "        return output\n",
    "    \n",
    "    def _add_GRU(self,units_number,activation=tf.nn.relu,keep_prob=1.0):\n",
    "        cell = tf.contrib.rnn.GRUCell(units_number,activation=activation)\n",
    "        cell = tf.contrib.rnn.DropoutWrapper(cell, input_keep_prob=keep_prob)\n",
    "        return cell\n",
    "    \n",
    "    def _add_GRUs(self,units_number,activation,keep_prob=1.0):\n",
    "        cells=tf.contrib.rnn.MultiRNNCell(cells=[ self._add_GRU(units_number=n,activation=a) for n,a in zip(units_number,activation)])\n",
    "        return cells\n",
    "    \n",
    "    def _add_gru_cell(self, units_number, activation=tf.nn.relu):\n",
    "        return tf.contrib.rnn.GRUCell(num_units=units_number, activation=activation)\n",
    "    \n",
    "    def train(self, drop=0.85):\n",
    "#         np.random.shuffle(random_index)\n",
    "        feed = {\n",
    "            self.a: np.transpose(np.array(self.a_buffer),axes=[1,0,2]),\n",
    "            self.r: np.transpose(np.array(self.r_buffer),axes=[1,0]),\n",
    "            self.s: np.transpose(np.array(self.s_buffer),axes=[1,0,2]),\n",
    "            self.s_next:np.transpose(np.array(self.s_next_buffer),axes=[1,0,2]),\n",
    "            self.dropout_keep_prob: drop\n",
    "        }\n",
    "        self.session.run([self.rltrain_op,self.sltrain_op], feed_dict=feed)\n",
    "    \n",
    "    def restore_buffer(self):\n",
    "        self.a_buffer = []\n",
    "        self.r_buffer = []\n",
    "        self.s_buffer = []\n",
    "        self.s_next_buffer=[]\n",
    "    \n",
    "    def save_current_state(self,s):\n",
    "        self.s_buffer.append(s)\n",
    "    \n",
    "    def save_transation(self, a, r,s_next):\n",
    "        self.a_buffer.append(a)\n",
    "        self.r_buffer.append(r)\n",
    "        self.s_next_buffer.append(s_next)\n",
    "    \n",
    "    def trade(self,train=False, drop=1.0, prob=False):\n",
    "#         print(np.array(self.a_buffer).shape)\n",
    "#         print(np.transpose(np.array(self.a_buffer),axes=[1,0,2]).shape)\n",
    "        feed = {\n",
    "            self.s: np.transpose(np.array(self.s_buffer),axes=[1,0,2]),\n",
    "            self.dropout_keep_prob: drop\n",
    "        }\n",
    "        a_prob = self.session.run([self.a_out], feed_dict=feed)[0]\n",
    "        \n",
    "        a_prob = a_prob[:,-1,:]\n",
    "        actions=[]\n",
    "        if train:\n",
    "            for ap in a_prob:\n",
    "                if prob:\n",
    "                    np.clip(np.random.normal(0.5,0.25),0,1)\n",
    "                else:\n",
    "                    a_indices = np.arange(ap.shape[0])\n",
    "                    target_index=np.random.choice(a_indices, p=ap)\n",
    "                    a=np.zeros(ap.shape[0])\n",
    "                    a[target_index]=1.0\n",
    "                    actions.append(a)\n",
    "            return np.array(actions)\n",
    "        else:\n",
    "            if prob:\n",
    "                return a_prob\n",
    "            actions=[]\n",
    "            for ap in a_prob:\n",
    "                target_index=np.argmax(ap)\n",
    "                a=np.zeros(ap.shape[0])\n",
    "                a[target_index]=1.0\n",
    "                actions.append(a)\n",
    "            return np.array(actions)\n",
    "        \n",
    "    def load_model(self, model_path='./RPGModel'):\n",
    "        self.saver.restore(self.session, model_path + '/model')\n",
    "\n",
    "    def save_model(self, model_path='./RPGModel'):\n",
    "        if not os.path.exists(model_path):\n",
    "            os.mkdir(model_path)\n",
    "        model_file = model_path + '/model'\n",
    "        self.saver.save(self.session, model_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.30774656, 0.87053765])"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.clip(np.random.normal([0,1],0.5),0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [],
   "source": [
    "# assets=['kanbtc','mdsbtc','socbtc','xrpbtc','dbcbtc','eosbtc','wiccbtc','letbtc']\n",
    "# assets=['kan','eos','mana']\n",
    "# assets=['kan','wicc','edu','eos','let']\n",
    "assets=['bat','let','mds']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [],
   "source": [
    "asset_data=lfilter(lambda x:x[1] is not None,lmap(lambda x:(x,kline(x,interval='60min',count=2000)),assets))\n",
    "asset_data=lmap(lambda x:(x[0],generate_tech_data_default(x[1],close_name='close',high_name='high',low_name='low',open_name='open')),asset_data)\n",
    "asset_data=dict(asset_data)\n",
    "asset_data=pd.Panel(asset_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.18827403"
      ]
     },
     "execution_count": 467,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_arbitrage(asset_data[:,1500:,'diff'].mean(axis=1).cumsum().values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f131fb5ea20>"
      ]
     },
     "execution_count": 468,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FrkPaY7eHA1In1Ls9zSZPUzkdBA+zNmZcL9Rj2CXJ0Tg7+cXvNmPsU3O1PgBH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\nvMYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12fe456f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset_data[:,:,'diff'].mean(axis=1).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 498,
   "metadata": {},
   "outputs": [],
   "source": [
    "model=RPG_Crypto_portfolio(action_size=2,feature_number=asset_data.shape[2],learning_rate=1e-4)\n",
    "model.init_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 499,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model.load_model(model_path='./PortfolioTrading/RPG_Portfolio_bat')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 500,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 train_reward -0.1616915400888754 -0.00010851781214018485\n",
      "0 test_reward 0.1075227679378066 0.0002609775920820549\n",
      "1 train_reward -0.37281094856014485 -0.00025020869030882196\n",
      "1 test_reward 0.15049735724563168 0.0003652848476835721\n",
      "2 train_reward -0.030119721286631936 -2.021457804471945e-05\n",
      "2 test_reward 0.19023555770197959 0.00046173679053878545\n",
      "3 train_reward 0.2045749140184064 0.00013729860001235325\n",
      "3 test_reward 0.2056867849100358 0.0004992397691991159\n",
      "4 train_reward -0.15941956360894033 -0.00010699299571069821\n",
      "4 test_reward 0.27458377535115075 0.0006664654741532785\n",
      "5 train_reward 0.19160555615391495 0.0001285943329892046\n",
      "5 test_reward 0.27307337314212304 0.0006627994493740851\n",
      "6 train_reward -0.10130625033362717 -6.799077203599139e-05\n",
      "6 test_reward 0.34058970452062864 0.0008266740400986131\n",
      "7 train_reward -0.0905996759217236 -6.080515162531791e-05\n",
      "7 test_reward 0.33343919102487696 0.0008093184248176624\n",
      "8 train_reward 0.17477251955891432 0.00011729699299255993\n",
      "8 test_reward 0.3456380555296713 0.0008389273192467748\n",
      "9 train_reward 0.26131597228744985 0.0001753798471727852\n",
      "9 test_reward 0.32841090724918603 0.0007971138525465682\n",
      "10 train_reward -0.023579896272139356 -1.5825433739690867e-05\n",
      "10 test_reward 0.34783731572297016 0.0008442653294246849\n",
      "11 train_reward 0.4587945659882729 0.00030791581609951205\n",
      "11 test_reward 0.29275698441622705 0.000710575204893755\n",
      "12 train_reward 0.36192306129749574 0.00024290138342113814\n",
      "12 test_reward 0.3424223895595898 0.0008311223047562859\n",
      "13 train_reward 0.428260199187875 0.0002874229524750839\n",
      "13 test_reward 0.35626081364725337 0.0008647107127360517\n",
      "14 train_reward 0.4619818518462805 0.0003100549341250204\n",
      "14 test_reward 0.3195371814877719 0.0007755756832227472\n",
      "15 train_reward 0.29452693531629226 0.0001976690841048941\n",
      "15 test_reward 0.3501147817542521 0.0008497931595976992\n",
      "16 train_reward 0.8380735403386913 0.0005624654633145579\n",
      "16 test_reward 0.3067861075590854 0.0007446264746579744\n",
      "17 train_reward 0.3050277183463622 0.00020471658949420285\n",
      "17 test_reward 0.30240496095179814 0.000733992623669413\n",
      "18 train_reward 0.42542051685956483 0.0002855171254091039\n",
      "18 test_reward 0.32063101188916643 0.0007782306113814717\n",
      "19 train_reward 0.4633148851944095 0.00031094958737879836\n",
      "19 test_reward 0.3327627496790879 0.00080767657689099\n",
      "20 train_reward 0.5851897247689453 0.00039274478172412434\n",
      "20 test_reward 0.3581140702225043 0.0008692089083070493\n",
      "21 train_reward 0.3809425894212399 0.0002556661673968053\n",
      "21 test_reward 0.3308522900333807 0.0008030395389159726\n",
      "22 train_reward 0.29309675622201165 0.00019670923236376624\n",
      "22 test_reward 0.3127376782523523 0.0007590720345930881\n",
      "23 train_reward 0.6262591912368001 0.00042030818203812073\n",
      "23 test_reward 0.36577071684104 0.0008877930020413594\n",
      "24 train_reward 0.30636183100083025 0.00020561196711465121\n",
      "24 test_reward 0.3246083879390538 0.0007878844367452762\n",
      "25 train_reward 0.4344737334489418 0.0002915931096972764\n",
      "25 test_reward 0.3030520736207557 0.0007355632854872711\n",
      "26 train_reward 0.7069078684062433 0.0004744348110109014\n",
      "26 test_reward 0.3133030635938475 0.0007604443291112804\n",
      "27 train_reward 0.6739573161465728 0.0004523203464070957\n",
      "27 test_reward 0.27591260260829625 0.0006696907830298452\n",
      "28 train_reward 0.6426083581272829 0.0004312807772666328\n",
      "28 test_reward 0.3279678480318119 0.0007960384660966309\n",
      "29 train_reward 0.5796726714804166 0.00038904206139625275\n",
      "29 test_reward 0.3475581061107844 0.0008435876361912241\n"
     ]
    }
   ],
   "source": [
    "normalize_length=10\n",
    "train_length=1500\n",
    "batch_size=60\n",
    "c=1e-5\n",
    "epoch=30\n",
    "train_r=[]\n",
    "train_mean_r=[]\n",
    "test_r=[]\n",
    "test_mean_r=[]\n",
    "model.restore_buffer()\n",
    "for e in range(epoch):\n",
    "    train_reward=[]\n",
    "    test_reward=[]\n",
    "    test_actions=[]\n",
    "    previous_action=np.zeros(asset_data.shape[0])\n",
    "    for t in range(normalize_length,train_length):\n",
    "        data=asset_data[:,t-normalize_length:t,:].values\n",
    "        state=((data-np.mean(data,axis=1,keepdims=True))/(np.std(data,axis=1,keepdims=True)+1e-5))[:,-1,:]\n",
    "        data=asset_data[:,t-normalize_length+1:t+1,:].values\n",
    "        next_state=((data-np.mean(data,axis=1,keepdims=True))/(np.std(data,axis=1,keepdims=True)+1e-5))[:,-1,:]\n",
    "        model.save_current_state(s=state)\n",
    "        action=model.trade(train=True,prob=False,drop=1.0)\n",
    "        r=asset_data[:,:,'diff'].iloc[t].values*action[:,0]-c*np.abs(previous_action-action[:,0])\n",
    "        model.save_transation(a=action,r=r,s_next=next_state)\n",
    "        previous_action=action[:,0]\n",
    "        train_reward.append(r)\n",
    "        if t%batch_size==0:\n",
    "            model.train(drop=0.8)\n",
    "            model.restore_buffer()\n",
    "    model.restore_buffer()\n",
    "    print(e,'train_reward',np.sum(np.mean(train_reward,axis=1)),np.mean(train_reward))\n",
    "    train_r.append(np.sum(np.mean(train_reward,axis=1)))\n",
    "    train_mean_r.append(np.mean(train_reward))\n",
    "    previous_action=np.zeros(asset_data.shape[0])\n",
    "    for t in range(train_length,asset_data.shape[1]):\n",
    "        data=asset_data[:,t-normalize_length:t,:].values\n",
    "        state=((data-np.mean(data,axis=1,keepdims=True))/(np.std(data,axis=1,keepdims=True)+1e-5))[:,-1,:]\n",
    "        model.save_current_state(s=state)\n",
    "        action=model.trade(train=False,prob=False,drop=1.0)\n",
    "        r=asset_data[:,:,'diff'].iloc[t].values*action[:,0]-c*np.abs(previous_action-action[:,0])\n",
    "        test_reward.append(r)\n",
    "        test_actions.append(action)\n",
    "        previous_action=action[:,0]\n",
    "        if t % batch_size==0:\n",
    "            model.restore_buffer()\n",
    "    print(e,'test_reward',np.sum(np.mean(test_reward,axis=1)),np.mean(test_reward))\n",
    "    test_r.append(np.sum(np.mean(test_reward,axis=1)))\n",
    "    test_mean_r.append(np.mean(test_reward))\n",
    "    model.restore_buffer()\n",
    "    if np.sum(np.mean(test_reward,axis=1))>0.45: break\n",
    "model.restore_buffer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 472,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f12fc255550>]"
      ]
     },
     "execution_count": 472,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tkcTbizazaVe52eUctbb4ANe9/Rs2h2bmxL7Oixt8j/T5izOal1dMeZWNcfWd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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12fc2c44a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(train_r)\n",
    "plt.plot(test_r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 473,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f131fb7c588>]"
      ]
     },
     "execution_count": 473,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zg7s3KflE46lyTSShzhJJ+Hv2i9W85Q5U33thG6/DCbqdB7J59dv1TElOo1p0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\nEokxxpiAWCIxxhgTkP8PoMcGhqGI8CUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12fc0f7dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(train_mean_r)\n",
    "plt.plot(test_mean_r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f12f655b518>"
      ]
     },
     "execution_count": 474,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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A6Nq2gAsensOY22fxl9nrQ/sTzYQaj91xeOLgri0+l5PXK0T7DvQHTMbPU3CL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\nmXXPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12f651bf28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset_data[:,:,'diff'].sum(axis=1).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_reward=np.mean(np.array(train_reward),axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 476,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f12f659ac88>"
      ]
     },
     "execution_count": 476,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FrHEYdR1XgjrUnm48bYujp44/YV1S3LdUbYuLHWt8vNZFtdmClUeWVYsY/qTS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\ngv8Dq46B0KaRgjgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12f6380dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.DataFrame(train_reward,index=asset_data[:,normalize_length:train_length,'diff'].index,columns=['return']).cumsum().plot()\n",
    "asset_data[:,normalize_length:train_length,'diff'].sum(axis=1).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_reward=np.mean(test_reward,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f12f6384c88>"
      ]
     },
     "execution_count": 478,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SU/zTRV2hRd/u2ZgHCWp4lJT+WH58G/x1YWg4p69d7LdYjY5Mkm6x61gzr396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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12f632f908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.DataFrame(test_reward,index=asset_data[:,train_length:,'diff'].index,columns=['return']).cumsum().plot()\n",
    "asset_data[:,train_length:,'diff'].sum(axis=1).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {},
   "outputs": [],
   "source": [
    "def maxdrawdown(arr):\n",
    "    i = np.argmax((np.maximum.accumulate(arr) - arr))  # end of the period\n",
    "    j = np.argmax(arr[:i])  # start of period\n",
    "    return (arr[j] - arr[i])\n",
    "\n",
    "def max_arbitrage(arr):\n",
    "    return maxdrawdown(arr[::-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_actions=np.array(test_actions)[:,:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f12f6261be0>"
      ]
     },
     "execution_count": 481,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1/TbgCuAq2ytGj26nOkXsw+V6HvAk8B9sv5Xq5K7rarmuBv6W6ujwKcDJbdp7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i4iIiIiImKP5vzs8k+/9HQal6S9qSZ6rrd9Uyl+TNJhtjeUV202dkkzEXjI9uMl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7jYiIiIiIiIho6HmyR9K+wM1Ujz49Vb9m29B556byKNZM4AjgEGAfSR8YRV8HqFbo/Nj2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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12fe437eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_action_df=pd.DataFrame(test_actions,index=asset_data[:,train_length:,'diff'].index,columns=list(asset_data.items))\n",
    "plt.figure(figsize=(18,30))\n",
    "sns.heatmap(test_action_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_length=asset_data.shape[1]-train_length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "metadata": {},
   "outputs": [],
   "source": [
    "def backtest(asset_data, model, test_length,batch_size=60, normalize_length=10, c=1e-4):\n",
    "    test_reward = []\n",
    "    test_actions = []\n",
    "    previous_action=np.zeros(asset_data.shape[0])\n",
    "    for t in range(asset_data.shape[1]-test_length,asset_data.shape[1]):\n",
    "        data=asset_data[:,t-normalize_length:t,:].values\n",
    "        state=((data-np.mean(data,axis=1,keepdims=True))/(np.std(data,axis=1,keepdims=True)+1e-5))[:,-1,:]\n",
    "        model.save_current_state(s=state)\n",
    "        action=model.trade(train=False,prob=False,drop=1.0)\n",
    "        r=asset_data[:,:,'diff'].iloc[t].values*action[:,0]-c*np.abs(previous_action-action[:,0])\n",
    "        test_reward.append(r)\n",
    "        test_actions.append(action)\n",
    "        previous_action=action[:,0]\n",
    "        if t % batch_size==0:\n",
    "            model.restore_buffer()\n",
    "    model.restore_buffer()\n",
    "    print('back test_reward', np.sum(np.mean(test_reward,axis=1)))\n",
    "    return np.sum(np.mean(test_reward,axis=1)),test_actions,np.mean(test_reward,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "back test_reward 0.3993677653786222\n"
     ]
    }
   ],
   "source": [
    "_,test_actions,test_reward=backtest(asset_data,model,test_length=test_length,batch_size=60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f12f6172898>"
      ]
     },
     "execution_count": 491,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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j291C1GOe8O0q+saeLf6lZIl5otBS45aUEPHX5pK6W54kBGn5DwYCpR16KP4g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\nh4wxZ4jIYuBO4Nqgz500/oyGsbPjn+td5PV6oirKYJJN4x8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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f12f6177e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.DataFrame(test_reward,index=asset_data[:,-test_length:,'diff'].index,columns=['return']).cumsum().plot()\n",
    "asset_data[:,-test_length:,'diff'].sum(axis=1).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 492,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.18827403"
      ]
     },
     "execution_count": 492,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_arbitrage(asset_data[:,-test_length:,'diff'].mean(axis=1).cumsum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bat    45.0\n",
       "let    52.0\n",
       "mds    49.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 493,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.abs(test_action_df.shift(1)-test_action_df).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 494,
   "metadata": {},
   "outputs": [],
   "source": [
    "def real_trade(asset_data,model, assets, normalize_length=10,batch_size=30, debug=True):\n",
    "    test_reward = []\n",
    "    test_actions = []\n",
    "    model.restore_buffer()\n",
    "    previous_action=np.zeros(asset_data.shape[0])\n",
    "    for t in range(asset_data.shape[1]-batch_size,asset_data.shape[1]):\n",
    "        data=asset_data[:,t-normalize_length:t,:].values\n",
    "        state=((data-np.mean(data,axis=1,keepdims=True))/(np.std(data,axis=1,keepdims=True)+1e-5))[:,-1,:]\n",
    "        model.save_current_state(s=state)\n",
    "        action=model.trade(train=False,prob=False,drop=1.0)\n",
    "    action = list(zip(assets, action[:,0]))\n",
    "#     action = sorted(action, key=lambda x: x[1])\n",
    "    print('predict action', action)\n",
    "    return action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 495,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predict action [('bat', 0.0), ('let', 1.0), ('mds', 0.0)]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[('bat', 0.0), ('let', 1.0), ('mds', 0.0)]"
      ]
     },
     "execution_count": 495,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "real_trade(asset_data,model,assets=assets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 696,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save_model('./PortfolioTrading/RPG_Portfolio_shareV')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    ""
   ]
  }
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